Object detection using merged sensor data clusters

Abstract

Techniques for object detection based on sensor data are discussed herein. In some cases, the techniques described herein include determining that a first sensor data cluster and a second sensor data cluster are associated with the same object if the two clusters satisfy a set of conditions. For example, a condition may be defined based on at least one of: (i) whether the second cluster is within an azimuth range associated with the first cluster, (ii) whether a height difference associated with the two clusters falls below a threshold, (iii) whether an aspect ratio associated with a combination of the two clusters is acceptable (e.g., satisfies at least one of one or more predefined aspect ratio conditions, falls within one of one or more predefined aspect ratio ranges, and/or the like), and/or (iv) whether cluster tracks associated with the two clusters jointly move across time.